Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response.
Jay A MooreKuei-Ting ChenRussell W MadisonJustin Y NewbergZoe FleischmannShuoguo WangRadwa SharafKarthikeyan MurugesanBernard J FendlerJason HughesAlexa B SchrockPriti S HegdeGeoffrey R OxnardDavid FabrizioGarrett M FramptonEmmanuel S AntonarakisEthan S SokolDexter X JinPublished in: JCO precision oncology (2023)
Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.
Keyphrases
- papillary thyroid
- copy number
- genome wide
- lymph node metastasis
- machine learning
- squamous cell
- mitochondrial dna
- prostate cancer
- dna damage
- dna repair
- dna methylation
- squamous cell carcinoma
- childhood cancer
- intellectual disability
- oxidative stress
- young adults
- body composition
- autism spectrum disorder
- benign prostatic hyperplasia
- data analysis